The invention relates to electrocardiography, and more particularly to an improved electrocardiographic system and method for predicting potential ventricular tachycardia and other forms of cardiac arrhythmia.
Sudden death from acute cardiac arrhythmia, in particular ventricular tachycardia, is a major risk in the first few hours after a myocardial infarction. During the first days after a myocardial infarction the incidence of ventricular arrhythmia is approximately 90%. The percentage of arrhythmias decreases considerably after the first several days but still presents a substantial risk to the myocardial infarct patient. Statistically, without treatment, approximately 50% of all myocardial infarct patients will eventually die of ventricular tachycardia.
U.S. Pat. No. 4,458,692 for System and Method for Predicting Ventricular Tachycardia With a Gain Controlled High Pass Filter, which issued to Michael Simson, teaches how a series of successive ECG waveforms may be captured, converted into digital form, and averaged together (after the exclusion of abnormal or nontypical waveforms) to provide a relatively noise-free composite waveform. Simson filters this averaged waveform using reverse or bidirectional filtering with a high-pass filter having a corner frequency of 25 Hz. Simson then computes the root-mean-square (RMS) value of the voltage in the filtered tail segment of the QRS complex. In addition, Simson measures the width of the QRS complex after the filtering. Simson uses this RMS voltage measurement and this width measurement as indications of whether or not the patient is likely to be subject to ventricular tachycardia.
The Simson method just described is inapplicable to patients suffering from bundle branch block, and it cannot always distinguish between meaningful high frequency components at the trailing edge of the QRS complex, which may indicate a predisposition to ventricular tachycardia, and noise that originates from power line disturbances or muscles or the like.
More recently, in an effort to extract more useful diagnostic information from the ECG signal, researchers have utilized Fourier transformations to process ECG waveforms. See, for example, FIG. 2 in an article by Michael E. Cain, et al., entitled, "Quantification of Differences in Frequency Content of Signal-Averaged Electrocardiograms in Patients With Compared To Those Without Sustained Ventricular Tachycardia," Vol. 55, American Journal of Cardiology, 1500 (June 1, 1985). That figure shows a frequency domain representation of the X, Y, and Z lead signals from patients with and without ventricular tachycardia. Energy, expressed as voltage squared, is plotted against frequency. Cain et al. teach that "frequencies above 70 Hz did not contribute substantially to the terminal QRS and ST segments in any group." Frequencies between 50 Hz and 70 Hz were not analyzed by Cain et al. because of potential 60 Hz power line interference. The Cain 25 et al. analysis was limited to a single Fourier transformation of a lengthy segment that included both the 40 millisecond terminal portion of the QRS complex and also the entire ST part of an averaged ECG waveform preprocessed with a Blackman-Harris window function to minimize spectral leakage. Cain et al.'s rationale for performing Fourier analysis of such an extended length segment, treating it as a single unit, was to "enhance frequency resolution." Cain et al.'s analysis of the frequency domain data was limited to the frequency range of from 20 Hz to 50 Hz.
While these prior art approaches to the problem both recognize that the presence of high frequency components in the trailing portions of the QRS complex can identify patients likely to experience cardiac arrhythmia, these approaches do not adequately address the practical problem of providing the physician with clear and unambiguous information presented in a form that is simple to understand and utilize. These approaches also do not enable the physician to distinguish high frequency components indicative of cardiac arrhythmia from high frequency components attributable to muscle noise and the like.